Instructions to use rendchevi/text-to-code-v0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rendchevi/text-to-code-v0.1 with Transformers:
# Load model directly from transformers import SpeakerConditionedCausalLM model = SpeakerConditionedCausalLM.from_pretrained("rendchevi/text-to-code-v0.1", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Model save
Browse files- config.json +1 -1
- model.safetensors +2 -2
config.json
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"speaker_token_id": 194246,
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"transformers_version": "5.6.2",
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"use_cache": false,
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"vocab_size":
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}
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"speaker_token_id": 194246,
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"transformers_version": "5.6.2",
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"use_cache": false,
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"vocab_size": 194256
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:0a6935093f4c2661e4867b0fa93063b216874cf79cf62308f8cde0ecb9ca09ef
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size 915437728
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